pplot (version 0.9)

pplot.t.test: Generate p-plot from a series of data points

Description

Takes a series of data points and computes either a chronological or ordered p-plot for testing the mean of the data points against 0 with a one-sample t-test.

Usage

pplot.t.test(data,
             sort = FALSE,
             startindex = 2,
             produce.plot = TRUE,
             xtitle = "Observation",
             plottype = 3,
             alpha = 0.05,
             alternative = "two.sided",
             n.sig = TRUE,
             n.sig.adjust = -1,
             ylim.p = c(0,1),
             ylim.es = -1,
             conf.level = 0.95,
             pcol.alpha = 125)

Value

pplot.t.test() returns either a vector of p-values, a data frame containing effect size estimates, or both (depending on the plottype argument).

Arguments

data

Vector of data points.

sort

Logical. TRUE generates an ordered p-plot, FALSE generates a chronological p-plot.

startindex

Number of observations to begin the p-plot with (minimum 2).

produce.plot

Logical whether to produce plot or not. Setting to FALSE can be used to extract series of p-values as well as effect size estimates from the data.

xtitle

Axis title for the x-axis of the p-plot.

plottype

1 = only p-plot, 2 = only effect size plot, 3 = both plots.

alpha

Significance threshold to be used for determining oversampling.

alternative

Argument passed on to the t.test() function (see the corresponding documentation).

n.sig

Logical: Show vertical line at last crossing of the significance threshold?

n.sig.adjust

-1 = auto, 0 = left-adjusted, 0.5 = centered, 1 = right.

ylim.p

Plot limits on the y-axis of the p-plot. Vector of min, max.

ylim.es

Plot limits on the y-axis of the effect size plot. Either a vector of min and max, or only one value to be used as minimum with maximum being determined as a function of the data.

conf.level

Confidence level for effect size CIs.

pcol.alpha

Transparency of the data points; set to 255 for solid fill.

Author

Roland Pfister

Details

pplot.t.test generates a chronological or ordered p-plot from a vector of data points. It returns a vector of p-values, or a data frame containing p-values and effect size estimates.

See Also

pplot.pvals; ci.sm;

Examples

# Show p-plot for significant test (the simulation 
# has a power of > 88% to return a significant 
# effect).
testdata <- rnorm(64, mean = 0.4, sd = 1)
pplot.t.test(testdata)

# Show p-plot for non-significant test (simulation 
# does not include a true effect).
testdata <- rnorm(64, mean = 0.0, sd = 1)
pplot.t.test(testdata)